{"id":38862,"date":"2024-11-02T01:39:38","date_gmt":"2024-11-02T01:39:38","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=38862"},"modified":"2024-11-26T06:43:09","modified_gmt":"2024-11-26T06:43:09","slug":"yolo-%eb%aa%a8%eb%8d%b8%ec%9d%98-%ed%8c%8c%eb%9d%bc%eb%af%b8%ed%84%b0-%ed%8a%9c%eb%8b%9d-%ec%8b%a0%eb%a2%b0%eb%8f%84%ec%99%80-iou-intersection-over-union-%ec%9e%84%ea%b3%84%ea%b0%92-%ec%a1%b0","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/38862\/","title":{"rendered":"YOLO \ubaa8\ub378\uc758 \ud30c\ub77c\ubbf8\ud130 \ud29c\ub2dd, \uc2e0\ub8b0\ub3c4\uc640 IOU (Intersection over Union) \uc784\uacc4\uac12 \uc870\uc815"},"content":{"rendered":"<p>YOLO(You Only Look Once) \ubaa8\ub378\uc740 \uc2e4\uc2dc\uac04 \uac1d\uccb4 \ud0d0\uc9c0\uc5d0\uc11c \ub6f0\uc5b4\ub09c \uc131\ub2a5\uc744 \ubcf4\uc5ec\uc8fc\ub294 \ub525\ub7ec\ub2dd \ubaa8\ub378\uc785\ub2c8\ub2e4. \uc5ec\ub7ec \uac00\uc9c0 \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc5d0 \ub110\ub9ac \uc0ac\uc6a9\ub418\uace0 \uc788\uc73c\uba70, \ub2e4\uc591\ud55c \uc544\ud0a4\ud14d\ucc98 \ubc84\uc804\uc774 \uc874\uc7ac\ud569\ub2c8\ub2e4. YOLO\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc88b\uc740 \uacb0\uacfc\ub97c \uc5bb\uae30 \uc704\ud574\uc11c\ub294 \ud30c\ub77c\ubbf8\ud130 \ud29c\ub2dd\uc774 \ud544\uc218\uc801\uc785\ub2c8\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 YOLO \ubaa8\ub378\uc758 \uc8fc\uc694 \ud30c\ub77c\ubbf8\ud130 \ud29c\ub2dd, \uc2e0\ub8b0\ub3c4 \ubc0f IOU(Intersection over Union) \uc784\uacc4\uac12 \uc870\uc815\uc5d0 \ub300\ud574 \uc790\uc138\ud788 \uc54c\uc544\ubcf4\ub3c4\ub85d \ud558\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n<h2>1. YOLO \ubaa8\ub378 \ud30c\ub77c\ubbf8\ud130 \uc774\ud574\ud558\uae30<\/h2>\n<p>YOLO \ubaa8\ub378\uc740 \uc5ec\ub7ec \ud558\uc774\ud37c\ud30c\ub77c\ubbf8\ud130\ub97c \uac00\uc9c0\uace0 \uc788\uc73c\uba70, \uc774\ub97c \uc870\uc815\ud568\uc73c\ub85c\uc368 \ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \ud06c\uac8c \ud5a5\uc0c1\uc2dc\ud0ac \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc8fc\uc694 \ud558\uc774\ud37c\ud30c\ub77c\ubbf8\ud130\ub294 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4:<\/p>\n<ul>\n<li><strong>Learning Rate:<\/strong> \ubaa8\ub378\uc774 \uac00\uc911\uce58\ub97c \uc5c5\ub370\uc774\ud2b8\ud558\ub294 \uc18d\ub3c4\ub97c \uacb0\uc815\ud569\ub2c8\ub2e4. \ub108\ubb34 \ub0ae\uc73c\uba74 \ud559\uc2b5\uc774 \ub290\ub824\uc9c0\uace0, \ub108\ubb34 \ub192\uc73c\uba74 \uc548\uc815\uc131\uc744 \uc783\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<li><strong>Batch Size:<\/strong> \ud55c \ubc88\uc5d0 \ub124\ud2b8\uc6cc\ud06c\uc5d0 \uc785\ub825\ud558\ub294 \ud6c8\ub828 \uc0d8\ud50c\uc758 \uc218\uc785\ub2c8\ub2e4. \ud070 \ubc30\uce58 \ud06c\uae30\ub294 \uc77c\ubc18\uc801\uc73c\ub85c \ub354 \ube60\ub978 \ud559\uc2b5\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.<\/li>\n<li><strong>Epochs:<\/strong> \uc804\uccb4 \ub370\uc774\ud130\uc14b\uc5d0 \ub300\ud574 \ub124\ud2b8\uc6cc\ud06c\ub97c \ubc18\ubcf5\ud574\uc11c \ud559\uc2b5\ud558\ub294 \ud69f\uc218\uc785\ub2c8\ub2e4. \ub108\ubb34 \ub9ce\uc740 epochs\ub294 \uacfc\uc801\ud569(overfitting)\uc744 \ucd08\ub798\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<li><strong>IOU Threshold:<\/strong> \uac1d\uccb4 \ud0d0\uc9c0\uc5d0\uc11c \uc608\uce21\ub41c \uacbd\uacc4 \uc0c1\uc790\uc640 \uc2e4\uc81c \uacbd\uacc4 \uc0c1\uc790 \uc0ac\uc774\uc758 \uc720\uc0ac\uc131\uc744 \uce21\uc815\ud558\ub294 \ucc99\ub3c4\uc785\ub2c8\ub2e4. \uc774 \uac12\uc744 \uc870\uc815\ud568\uc73c\ub85c\uc368 \ud0d0\uc9c0 \uc131\ub2a5\uc744 \uc870\uc808\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<li><strong>Confidence Threshold:<\/strong> \uac1d\uccb4 \ud0d0\uc9c0 \uacb0\uacfc\uc758 \uc2e0\ub8b0\ub3c4\ub97c \ub098\ud0c0\ub0b4\ub294 \uac12\uc785\ub2c8\ub2e4. \uc774 \uac12\uc5d0 \ub530\ub77c \ud0d0\uc9c0 \uc131\ub2a5\uc5d0 \uc601\ud5a5\uc744 \ubbf8\uce58\uac8c \ub429\ub2c8\ub2e4.<\/li>\n<\/ul>\n<h2>2. \uc2e0\ub8b0\ub3c4(score)\uc640 IOU \uc784\uacc4\uac12 \uc870\uc815<\/h2>\n<p>\uc5ec\uae30\uc11c \uc2e0\ub8b0\ub3c4\uc640 IOU\ub294 \ubaa8\ub378\uc758 \uc608\uce21 \uc131\ub2a5\uc744 \ud3c9\uac00\ud558\ub294 \ub450 \uac00\uc9c0 \uc911\uc694\ud55c \uc694\uc18c\uc785\ub2c8\ub2e4.<\/p>\n<h3>2.1 \uc2e0\ub8b0\ub3c4 \uc870\uc815<\/h3>\n<p>\uc2e0\ub8b0\ub3c4 \uac12\uc740 \ubaa8\ub378\uc774 \uac1d\uccb4\ub97c \ud0d0\uc9c0\ud588\uc744 \ub54c\uc758 \ud655\ub960\uc744 \ub098\ud0c0\ub0b4\uba70, \ubcf4\ud1b5 0\uacfc 1 \uc0ac\uc774\uc758 \uac12\uc744 \uac00\uc9d1\ub2c8\ub2e4. \uc2e0\ub8b0\ub3c4 \uc784\uacc4\uac12\uc744 \uc870\uc815\ud558\uc5ec \uac10\uc9c0\uc758 \ubbfc\uac10\ub3c4\uc640 \uc815\ubc00\ub3c4\ub97c \ud29c\ub2dd\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<p>\uc608\ub97c \ub4e4\uc5b4, \uc2e0\ub8b0\ub3c4 \uc784\uacc4\uac12\uc744 0.5\ub85c \uc124\uc815\ud558\uba74 \ud0d0\uc9c0\ub41c \uac1d\uccb4\uac00 50% \uc774\uc0c1\uc758 \uc2e0\ub8b0\ub3c4\ub97c \uac00\uc9c4 \uacbd\uc6b0\ub9cc \uc2dc\uac01\ud654\ub429\ub2c8\ub2e4. \uc774 \uc784\uacc4\uac12\uc744 \ub192\uc774\uba74 \ub354 \uc815\ud655\ud55c \ud0d0\uc9c0 \uacb0\uacfc\ub97c \uc5bb\uc744 \uc218 \uc788\uc9c0\ub9cc, \ud0d0\uc9c0\ud560 \uc218 \uc788\ub294 \uac1d\uccb4\uc758 \uc218\uac00 \uc904\uc5b4\ub4e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub97c \uace0\ub824\ud558\uc5ec \uc2e0\ub8b0\ub3c4 \uc784\uacc4\uac12\uc744 \uc870\uc815\ud558\ub294 \uac83\uc774 \uc911\uc694\ud569\ub2c8\ub2e4.<\/p>\n<h3>2.2 IOU \uc784\uacc4\uac12 \uc870\uc815<\/h3>\n<p>IOU(Intersection over Union)\ub294 \uc608\uce21\ub41c \uacbd\uacc4 \uc0c1\uc790\uc640 \uc2e4\uc81c \uacbd\uacc4 \uc0c1\uc790 \uac04\uc758 \uacb9\uce58\ub294 \ube44\uc728\uc744 \uce21\uc815\ud558\ub294 \uc911\uc694\ud55c \uc9c0\ud45c\uc785\ub2c8\ub2e4. IOU \uac12\uc774 \ub192\uc744\uc218\ub85d \ub450 \uc0c1\uc790\ub294 \ub354 \uc798 \uacb9\uce58\uac8c \ub429\ub2c8\ub2e4. IOU \uc784\uacc4\uac12\uc744 \uc870\uc815\ud568\uc73c\ub85c\uc368 \ud0d0\uc9c0 \uc131\ub2a5\uc744 \ud070 \ud3ed\uc73c\ub85c \ubcc0\ud654\uc2dc\ud0ac \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc77c\ubc18\uc801\uc73c\ub85c IOU \uc784\uacc4\uac12\uc740 0.5\ub85c \uc124\uc815\ub418\uc9c0\ub9cc, \uc0c1\ud669\uc5d0 \ub530\ub77c \uc774 \uac12\uc744 \uc870\uc815\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<p>\uc608\ub97c \ub4e4\uc5b4, \ub192\uc740 IOU \uc784\uacc4\uac12\uc744 \uc124\uc815\ud558\ub294 \uac83\uc740 \uc815\ud655\ud55c \ud0d0\uc9c0\ub97c \uc694\uad6c\ud558\uc9c0\ub9cc, \ubc18\uba74\uc5d0 \ub9ce\uc740 \uac1d\uccb4\uac00 \ud0d0\uc9c0\ub418\uc9c0 \uc54a\uc744 \uc704\ud5d8\uc774 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \uc810\uc744 \uc798 \uace0\ub824\ud558\uc5ec \ucd5c\uc801\uc758 \uc784\uacc4\uac12\uc744 \uacb0\uc815\ud574\uc57c \ud569\ub2c8\ub2e4.<\/p>\n<h2>3. \ud30c\ub77c\ubbf8\ud130 \ud29c\ub2dd\uc744 \uc704\ud55c \uc608\uc81c<\/h2>\n<p>PythoN\uacfc OpenCV\ub97c \uc0ac\uc6a9\ud558\uc5ec YOLO \ubaa8\ub378\uc744 \uad6c\ud604\ud558\uace0 \uc2e0\ub8b0\ub3c4 \ubc0f IOU \uc784\uacc4\uac12\uc744 \uc870\uc815\ud558\ub294 \uac04\ub2e8\ud55c \uc608\uc81c\ub97c \uc0b4\ud3b4\ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n<h3>3.1 \ub77c\uc774\ube0c\ub7ec\ub9ac \uc124\uce58<\/h3>\n<p>YOLO \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud558\uae30 \uc704\ud574 \ud544\uc694\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc124\uce58\ud569\ub2c8\ub2e4.<\/p>\n<pre><code>!pip install opencv-python numpy<\/code><\/pre>\n<h3>3.2 YOLO \ubaa8\ub378 \ubd88\ub7ec\uc624\uae30<\/h3>\n<p>YOLO \ubaa8\ub378\uc744 \ubd88\ub7ec\uc624\ub294 \ucf54\ub4dc\ub294 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4. \uc5ec\uae30\uc5d0 YOLOv3\uc758 \uac00\uc911\uce58\uc640 \uad6c\uc131 \ud30c\uc77c\uc744 \uc0ac\uc6a9\ud569\ub2c8\ub2e4.<\/p>\n<pre><code>\nimport cv2\nimport numpy as np\n\n# YOLO \ubaa8\ub378 \ub85c\ub4dc\ndef load_yolo_model():\n    net = cv2.dnn.readNet(\"yolov3.weights\", \"yolov3.cfg\")\n    return net\n\n# \ud074\ub798\uc2a4 \uc774\ub984 \ub85c\ub4dc\ndef load_classes():\n    with open(\"coco.names\", \"r\") as f:\n        classes = [line.strip() for line in f.readlines()]\n    return classes\n<\/code><\/pre>\n<h3>3.3 \uc774\ubbf8\uc9c0\uc5d0\uc11c \uac1d\uccb4 \ud0d0\uc9c0\ud558\uae30<\/h3>\n<p>\ub2e4\uc74c \ucf54\ub4dc\ub294 \uc774\ubbf8\uc9c0\ub97c YOLO \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud558\uc5ec \uac1d\uccb4\ub97c \ud0d0\uc9c0\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. \uc2e0\ub8b0\ub3c4\uc640 IOU \uc784\uacc4\uac12\uc744 \uc870\uc815\ud558\ub294 \ubd80\ubd84\ub3c4 \ud3ec\ud568\ub418\uc5b4 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<pre><code>\ndef detect_objects(image, net, classes, confidence_threshold=0.5, iou_threshold=0.5):\n    height, width, _ = image.shape\n\n    # YOLO\uc5d0 \uc785\ub825\uc73c\ub85c \uc0ac\uc6a9\ud560 \uc900\ube44\n    blob = cv2.dnn.blobFromImage(image, 0.00392, (416, 416), (0, 0, 0), True, crop=False)\n    net.setInput(blob)\n\n    # \ub808\uc774\uc5b4 \ucd9c\ub825 \ucd94\ucd9c\n    layer_names = net.getLayerNames()\n    output_layers = [layer_names[i[0] - 1] for i in net.getUnconnectedOutLayers()]\n    outputs = net.forward(output_layers)\n\n    boxes = []\n    confidences = []\n    class_ids = []\n\n    # \ud0d0\uc9c0 \uacb0\uacfc \ud544\ud130\ub9c1\n    for output in outputs:\n        for detection in output:\n            scores = detection[5:]\n            class_id = np.argmax(scores)\n            confidence = scores[class_id]\n\n            if confidence &gt; confidence_threshold:\n                center_x = int(detection[0] * width)\n                center_y = int(detection[1] * height)\n                w = int(detection[2] * width)\n                h = int(detection[3] * height)\n\n                x = int(center_x - w \/ 2)\n                y = int(center_y - h \/ 2)\n\n                boxes.append([x, y, w, h])\n                confidences.append(float(confidence))\n                class_ids.append(class_id)\n\n    # \ube44\ucd5c\ub300 \uc5b5\uc81c(NMS)\ub97c \uc801\uc6a9\ud558\uc5ec \ucd5c\uc885 \ud0d0\uc9c0 \uacb0\uacfc \ud68d\ub4dd\n    indices = cv2.dnn.NMSBoxes(boxes, confidences, confidence_threshold, iou_threshold)\n\n    detected_objects = []\n    for i in indices:\n        box = boxes[i[0]]\n        x, y, w, h = box\n        detected_objects.append({\n            \"class_id\": class_ids[i[0]],\n            \"confidence\": confidences[i[0]],\n            \"box\": (x, y, w, h)\n        })\n\n    return detected_objects\n<\/code><\/pre>\n<h3>3.4 \uacb0\uacfc \uc2dc\uac01\ud654<\/h3>\n<p>\ud0d0\uc9c0\ub41c \uac1d\uccb4\ub97c \uc2dc\uac01\ud654\ud558\ub294 \ud568\uc218\ub294 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/p>\n<pre><code>\ndef draw_labels(image, detected_objects, classes):\n    for obj in detected_objects:\n        x, y, w, h = obj['box']\n        label = f\"{classes[obj['class_id']]}: {obj['confidence']:.2f}\"\n        cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)\n        cv2.putText(image, label, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)\n    \n    return image\n<\/code><\/pre>\n<h3>3.5 \uc804\uccb4 \ucf54\ub4dc \uc2e4\ud589\ud558\uae30<\/h3>\n<p>\ubaa8\ub4e0 \ubd80\ubd84\uc744 \uacb0\ud569\ud558\uc5ec \uc774\ubbf8\uc9c0\ub97c \ud0d0\uc9c0\ud558\ub294 \uc804\uccb4 \ucf54\ub4dc\ub294 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/p>\n<pre><code>\n# \ucd08\uae30\ud654\nnet = load_yolo_model()\nclasses = load_classes()\n\n# \uc774\ubbf8\uc9c0 \ub85c\ub4dc\nimage = cv2.imread(\"input.jpg\")\n\n# \uac1d\uccb4 \ud0d0\uc9c0\ndetected_objects = detect_objects(image, net, classes, confidence_threshold=0.5, iou_threshold=0.5)\n\n# \uacb0\uacfc \uc2dc\uac01\ud654\nresult_image = draw_labels(image, detected_objects, classes)\n\n# \uacb0\uacfc \uc774\ubbf8\uc9c0 \ucd9c\ub825\ncv2.imshow(\"YOLO Object Detection\", result_image)\ncv2.waitKey(0)\ncv2.destroyAllWindows()\n<\/code><\/pre>\n<h2>4. YOLO \ud30c\ub77c\ubbf8\ud130 \ud29c\ub2dd\uc5d0 \ub300\ud55c \ud301<\/h2>\n<p>YOLO \ubaa8\ub378\uc744 \ud6a8\uacfc\uc801\uc73c\ub85c \ud29c\ub2dd\ud558\ub824\uba74 \ub2e4\uc74c\uacfc \uac19\uc740 \ud301\uc774 \uc788\uc2b5\ub2c8\ub2e4:<\/p>\n<ul>\n<li>\ub370\uc774\ud130\uc14b\uc5d0 \ub530\ub978 \uc2e0\ub8b0\ub3c4 \ubc0f IOU \uc124\uc815\uc744 \ub2e4\ub974\uac8c \uc124\uc815\ud558\uc138\uc694. \ub2e4\uc591\ud55c \ub370\uc774\ud130\uc14b\uc5d0\uc11c\uc758 \uc131\uc548\uc744 \uace0\ub824\ud558\uc5ec \ucd5c\uc801\uc758 \ud30c\ub77c\ubbf8\ud130 \uc870\ud569\uc744 \ucc3e\uc544\uc57c \ud569\ub2c8\ub2e4.<\/li>\n<li>\ubaa8\ub378 \uc131\ub2a5\uc744 \uc815\uae30\uc801\uc73c\ub85c \uccb4\ud06c\ud558\uc5ec \ucd5c\uc801\uc758 \ud558\uc774\ud37c\ud30c\ub77c\ubbf8\ud130\ub97c \uacb0\uc815\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<li>\uac00\ub2a5\ud55c \uacbd\uc6b0, \ub2e4\ub978 \uc2e0\ub8b0\ub3c4\ub098 IOU \uc784\uacc4\uac12\uc744 \uc2dc\ub3c4\ud558\uc5ec \uc131\ub2a5\uc744 \ube44\uad50\ud558\uc138\uc694.<\/li>\n<li>Batch Size\uc640 Learning Rate\uc758 \uc801\uc808\ud55c \uc870\ud569\uc744 \ucc3e\uc544\uc57c \ud569\ub2c8\ub2e4. \uc774 \uac12\ub4e4\uc774 \uc601\ud5a5\uc744 \ubbf8\uce58\ub294 \ubc29\ubc95\uc744 \uc774\ud574\ud558\uace0 \uc2e4\ud5d8\ud558\uc138\uc694.<\/li>\n<\/ul>\n<h2>5. \uacb0\ub860<\/h2>\n<p>YOLO \ubaa8\ub378\uc758 \ud30c\ub77c\ubbf8\ud130 \ud29c\ub2dd \ubc0f \uc2e0\ub8b0\ub3c4\uc640 IOU \uc784\uacc4\uac12 \uc870\uc815\uc740 \ud6a8\uacfc\uc801\uc778 \uac1d\uccb4 \ud0d0\uc9c0\uc5d0\uc11c \ud575\uc2ec\uc801\uc778 \ubd80\ubd84\uc785\ub2c8\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 \ub2e4\uc591\ud55c \ud30c\ub77c\ubbf8\ud130\uc5d0 \ub300\ud55c \uc774\ud574\uc640 \uac04\ub2e8\ud55c \uc608\uc81c\ub97c \ud1b5\ud574 YOLO\uc758 \uc131\ub2a5\uc744 \ub192\uc774\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \uc124\uba85\ud558\uc600\uc2b5\ub2c8\ub2e4. \uc2e4\uc9c8\uc801\uc778 \uc2e4\ud5d8\uc744 \ud1b5\ud574 \uc790\uc2e0\uc758 \ub370\uc774\ud130\uc14b\uc5d0 \ub9de\ub294 \ucd5c\uc801\uc758 \ud558\uc774\ud37c\ud30c\ub77c\ubbf8\ud130\uc640 \uc784\uacc4\uac12 \uc870\uc815\uc744 \ucc3e\uc544\ubcf4\uc2dc\uae30 \ubc14\ub78d\ub2c8\ub2e4. \ucd5c\uc801\ud654 \uacfc\uc815\uc744 \ud1b5\ud574 \ubcf4\ub2e4 \ub098\uc740 \uc131\uacfc\ub97c \uc5bb\uc744 \uc218 \uc788\uc744 \uac83\uc785\ub2c8\ub2e4.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>YOLO(You Only Look Once) \ubaa8\ub378\uc740 \uc2e4\uc2dc\uac04 \uac1d\uccb4 \ud0d0\uc9c0\uc5d0\uc11c \ub6f0\uc5b4\ub09c \uc131\ub2a5\uc744 \ubcf4\uc5ec\uc8fc\ub294 \ub525\ub7ec\ub2dd \ubaa8\ub378\uc785\ub2c8\ub2e4. \uc5ec\ub7ec \uac00\uc9c0 \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc5d0 \ub110\ub9ac \uc0ac\uc6a9\ub418\uace0 \uc788\uc73c\uba70, \ub2e4\uc591\ud55c \uc544\ud0a4\ud14d\ucc98 \ubc84\uc804\uc774 \uc874\uc7ac\ud569\ub2c8\ub2e4. YOLO\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc88b\uc740 \uacb0\uacfc\ub97c \uc5bb\uae30 \uc704\ud574\uc11c\ub294 \ud30c\ub77c\ubbf8\ud130 \ud29c\ub2dd\uc774 \ud544\uc218\uc801\uc785\ub2c8\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 YOLO \ubaa8\ub378\uc758 \uc8fc\uc694 \ud30c\ub77c\ubbf8\ud130 \ud29c\ub2dd, \uc2e0\ub8b0\ub3c4 \ubc0f IOU(Intersection over Union) \uc784\uacc4\uac12 \uc870\uc815\uc5d0 \ub300\ud574 \uc790\uc138\ud788 \uc54c\uc544\ubcf4\ub3c4\ub85d \ud558\uaca0\uc2b5\ub2c8\ub2e4. 1. YOLO \ubaa8\ub378 \ud30c\ub77c\ubbf8\ud130 \uc774\ud574\ud558\uae30 &hellip; <a href=\"https:\/\/atmokpo.com\/w\/38862\/\" class=\"more-link\">\ub354 \ubcf4\uae30<span class=\"screen-reader-text\"> &#8220;YOLO \ubaa8\ub378\uc758 \ud30c\ub77c\ubbf8\ud130 \ud29c\ub2dd, \uc2e0\ub8b0\ub3c4\uc640 IOU (Intersection over Union) \uc784\uacc4\uac12 \uc870\uc815&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[189],"tags":[],"class_list":["post-38862","post","type-post","status-publish","format-standard","hentry","category-yolo"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>YOLO \ubaa8\ub378\uc758 \ud30c\ub77c\ubbf8\ud130 \ud29c\ub2dd, \uc2e0\ub8b0\ub3c4\uc640 IOU (Intersection over Union) \uc784\uacc4\uac12 \uc870\uc815 - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/atmokpo.com\/w\/38862\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"YOLO \ubaa8\ub378\uc758 \ud30c\ub77c\ubbf8\ud130 \ud29c\ub2dd, \uc2e0\ub8b0\ub3c4\uc640 IOU (Intersection over Union) \uc784\uacc4\uac12 \uc870\uc815 - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"og:description\" content=\"YOLO(You Only Look Once) \ubaa8\ub378\uc740 \uc2e4\uc2dc\uac04 \uac1d\uccb4 \ud0d0\uc9c0\uc5d0\uc11c \ub6f0\uc5b4\ub09c \uc131\ub2a5\uc744 \ubcf4\uc5ec\uc8fc\ub294 \ub525\ub7ec\ub2dd \ubaa8\ub378\uc785\ub2c8\ub2e4. \uc5ec\ub7ec \uac00\uc9c0 \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc5d0 \ub110\ub9ac \uc0ac\uc6a9\ub418\uace0 \uc788\uc73c\uba70, \ub2e4\uc591\ud55c \uc544\ud0a4\ud14d\ucc98 \ubc84\uc804\uc774 \uc874\uc7ac\ud569\ub2c8\ub2e4. YOLO\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc88b\uc740 \uacb0\uacfc\ub97c \uc5bb\uae30 \uc704\ud574\uc11c\ub294 \ud30c\ub77c\ubbf8\ud130 \ud29c\ub2dd\uc774 \ud544\uc218\uc801\uc785\ub2c8\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 YOLO \ubaa8\ub378\uc758 \uc8fc\uc694 \ud30c\ub77c\ubbf8\ud130 \ud29c\ub2dd, \uc2e0\ub8b0\ub3c4 \ubc0f IOU(Intersection over Union) \uc784\uacc4\uac12 \uc870\uc815\uc5d0 \ub300\ud574 \uc790\uc138\ud788 \uc54c\uc544\ubcf4\ub3c4\ub85d \ud558\uaca0\uc2b5\ub2c8\ub2e4. 1. 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